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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/10/11 17:49:23 UTC
[GitHub] [incubator-mxnet] NamLQ opened a new issue #16445: cuda.h: No such
file or directory
NamLQ opened a new issue #16445: cuda.h: No such file or directory
URL: https://github.com/apache/incubator-mxnet/issues/16445
## Description
I can not perform manual MXNet-R Installation on Ubuntu 18.04 LTS with cuda 10.1 and cudnn 7.6.4. The post-installation actions of cuda and cudnn had been performed successfully.
## Environment info (Required)
```
What to do:
1. Download the diagnosis script from https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py
2. Run the script using `python diagnose.py` and paste its output here.
----------Python Info----------
('Version :', '2.7.15+')
('Compiler :', 'GCC 7.4.0')
('Build :', ('default', 'Oct 7 2019 17:39:04'))
('Arch :', ('64bit', ''))
------------Pip Info-----------
('Version :', '19.2.3')
('Directory :', '/usr/local/lib/python2.7/dist-packages/pip')
----------MXNet Info-----------
('Version :', '1.5.1')
('Directory :', '/usr/local/lib/python2.7/dist-packages/mxnet')
('Commit Hash :', 'c9818480680f84daa6e281a974ab263691302ba8')
('Library :', ['/usr/local/lib/python2.7/dist-packages/mxnet/libmxnet.so'])
Build features:
✔ CUDA
✔ CUDNN
✔ NCCL
✔ CUDA_RTC
✖ TENSORRT
✔ CPU_SSE
✔ CPU_SSE2
✔ CPU_SSE3
✔ CPU_SSE4_1
✔ CPU_SSE4_2
✖ CPU_SSE4A
✔ CPU_AVX
✖ CPU_AVX2
✖ OPENMP
✖ SSE
✔ F16C
✖ JEMALLOC
✖ BLAS_OPEN
✖ BLAS_ATLAS
✖ BLAS_MKL
✖ BLAS_APPLE
✔ LAPACK
✖ MKLDNN
✔ OPENCV
✖ CAFFE
✖ PROFILER
✔ DIST_KVSTORE
✖ CXX14
✖ INT64_TENSOR_SIZE
✔ SIGNAL_HANDLER
✖ DEBUG
----------System Info----------
('Platform :', 'Linux-4.15.0-65-generic-x86_64-with-Ubuntu-18.04-bionic')
('system :', 'Linux')
('node :', 'machinelearning')
('release :', '4.15.0-65-generic')
('version :', '#74-Ubuntu SMP Tue Sep 17 17:06:04 UTC 2019')
----------Hardware Info----------
('machine :', 'x86_64')
('processor :', 'x86_64')
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 8
On-line CPU(s) list: 0-7
Thread(s) per core: 2
Core(s) per socket: 4
Socket(s): 1
NUMA node(s): 1
Vendor ID: AuthenticAMD
CPU family: 21
Model: 2
Model name: AMD FX(tm)-8350 Eight-Core Processor
Stepping: 0
CPU MHz: 1403.655
CPU max MHz: 4000.0000
CPU min MHz: 1400.0000
BogoMIPS: 8027.19
Virtualization: AMD-V
L1d cache: 16K
L1i cache: 64K
L2 cache: 2048K
L3 cache: 8192K
NUMA node0 CPU(s): 0-7
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 popcnt aes xsave avx f16c lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs xop skinit wdt fma4 tce nodeid_msr tbm topoext perfctr_core perfctr_nb cpb hw_pstate ssbd ibpb vmmcall bmi1 arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold
----------Network Test----------
Setting timeout: 10
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0046 sec, LOAD: 0.9385 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0035 sec, LOAD: 1.0756 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.8954 sec, LOAD: 0.3998 sec.
Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.2478 sec, LOAD: 0.2311 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.3526 sec, LOAD: 0.2759 sec.
Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.7199 sec, LOAD: 0.7465 sec.
----------Environment----------
```
I'm using R
```
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.3 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_3.6.1
```
## Build info (Required if built from source)
Compiler (gcc/clang/mingw/visual studio):
```
gcc --version
gcc (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0
```
MXNet commit hash: `cf61364a2f38c90769098b330d5ecbafc34d4ed2`
Build config for short:
```
# whether use CUDA during compile
USE_CUDA = 1
# choose the version of blas you want to use
# can be: mkl, blas, atlas, openblas
# in default use atlas for linux while apple for osx
UNAME_S := $(shell uname -s)
ifeq ($(UNAME_S), Darwin)
USE_BLAS = apple
else
USE_BLAS = openblas
endif
```
## Error Message:
```
Makefile:360: WARNING: Significant performance increases can be achieved by installing and enabling gperftools or jemalloc development packages
g++ -std=c++11 -c -DMSHADOW_FORCE_STREAM -Wall -Wsign-compare -O3 -DNDEBUG=1 -I/home/nam/Downloads/incubator-mxnet/3rdparty/mshadow/ -I/home/nam/Downloads/incubator-mxnet/3rdparty/dmlc-core/include -fPIC -I/home/nam/Downloads/incubator-mxnet/3rdparty/tvm/nnvm/include -I/home/nam/Downloads/incubator-mxnet/3rdparty/dlpack/include -I/home/nam/Downloads/incubator-mxnet/3rdparty/tvm/include -Iinclude -funroll-loops -Wno-unused-parameter -Wno-unknown-pragmas -Wno-unused-local-typedefs -msse3 -mf16c -I/include -DMSHADOW_USE_CBLAS=1 -DMSHADOW_USE_MKL=0 -I/home/nam/Downloads/incubator-mxnet/3rdparty/mkldnn/build/install/include -DMSHADOW_RABIT_PS=0 -DMSHADOW_DIST_PS=0 -DMSHADOW_USE_PASCAL=0 -DMXNET_USE_MKLDNN=1 -DUSE_MKL=1 -I/home/nam/Downloads/incubator-mxnet/src/operator/nn/mkldnn/ -I/home/nam/Downloads/incubator-mxnet/3rdparty/mkldnn/build/install/include -DMXNET_USE_OPENCV=1 -I/usr/include/opencv -DMSHADOW_INT64_TENSOR_SIZE=0 -DMXNET_USE_BLAS_OPEN=1 -DMXNET_USE_NCCL=0 -DMXNET_USE_LIBJPEG_TURBO=0 -MMD -c src/operator/quantization/mkldnn/mkldnn_quantized_elemwise_add.cc -o build/src/operator/quantization/mkldnn/mkldnn_quantized_elemwise_add.o
In file included from /home/nam/Downloads/incubator-mxnet/3rdparty/mshadow/mshadow/tensor.h:16:0,
from include/mxnet/./base.h:33,
from include/mxnet/operator_util.h:43,
from src/operator/quantization/mkldnn/../../tensor/elemwise_unary_op.h:28,
from src/operator/quantization/mkldnn/../quantized_elemwise_add-inl.h:28,
from src/operator/quantization/mkldnn/mkldnn_quantized_elemwise_add.cc:27:
/home/nam/Downloads/incubator-mxnet/3rdparty/mshadow/mshadow/./base.h:173:12: fatal error: cuda.h: No such file or directory
#include <cuda.h>
^~~~~~~~
compilation terminated.
Makefile:560: recipe for target 'build/src/operator/quantization/mkldnn/mkldnn_quantized_elemwise_add.o' failed
make: *** [build/src/operator/quantization/mkldnn/mkldnn_quantized_elemwise_add.o] Error 1
```
## Minimum reproducible example
(If you are using your own code, please provide a short script that reproduces the error. Otherwise, please provide link to the existing example.)
## Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
rm -rf build
mkdir -p build && cd build
cmake -GNinja \
-DUSE_CUDA=ON \
-DUSE_MKL_IF_AVAILABLE=OFF \
-DCMAKE_CUDA_COMPILER_LAUNCHER=ccache \
-DCMAKE_C_COMPILER_LAUNCHER=ccache \
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_BUILD_TYPE=Release \
..
ninja
cd ..
make
2.
## What have you tried to solve it?
1. Installed cuda 10.0, 9.2 and equivalent cudnn
2. Removed completely old cuda installation before installing new one.
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